Biomarker for distinguishing mood disorder type psychiatric disease and schizophrenia, and uses thereof

Abstract

The present invention relates to a biomarker for distinguishing mood disorder-type psychiatric diseases and schizophrenia, and uses thereof. Based on a biomarker composition for mood disorder-type psychiatric diseases and schizophrenia comprising the serum proteins including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF), the present invention describes a composition for distinguishing mood disorder-type psychiatric diseases and schizophrenia, comprising reagents for measuring the expression levels of the five biomarker proteins, and a method for providing information for distinguishing between mood disorder-type psychiatric diseases and schizophrenia, using same.

Description

Biomarkers for differentiating mood disorder and schizophrenia and their uses

[0001] The present invention relates to a biomarker for distinguishing between mood disorder-type mental illness and schizophrenia and its use.

[0002] While physical diseases such as internal or surgical diseases are diagnosed using imaging medical devices such as CT and MRI, or hematological medical devices such as biomarkers and diagnostic kits, the diagnosis of mental illness is currently focused on the clinical symptoms that are apparent on the surface.

[0003] In relation to these major mental illnesses, according to the World Health Report published by WHO in 2000, depression ranks first, schizophrenia third, and bipolar disorder fifth in statistics on YLD (Years Lived With Disability).

[0004] In particular, patients with mood disorders such as depression and bipolar disorder may commit suicide if they are not diagnosed and treated in a timely manner, and according to data from Statistics Korea, 80% of suicides are related to mood disorders.

[0005] Therefore, it is of utmost importance to detect and diagnose major mental illnesses such as depression, bipolar disorder, or schizophrenia at an early stage and to initiate treatment quickly.

[0006] However, clinical diagnostic tests performed to quickly diagnose major mental illnesses such as depression, bipolar disorder, or schizophrenia have certain limitations in terms of diagnostic accuracy and reliability.

[0007] For example, although depression and bipolar disorder are different mental illnesses, they both have symptoms of a 'depressive episode', so in clinical practice, 40% to 50% of bipolar disorder patients are misdiagnosed as having depression.

[0008] Another example is that bipolar disorder patients are sometimes misdiagnosed as schizophrenic due to delusions and hallucinations seen in the 'manic episodes' of bipolar disorder.

[0009] Because of this, when bipolar patients initially diagnosed with depression use antidepressants, the course of the disorder may worsen, either by inducing 'manic and hypomanic episodes' or by entering a rapid cycling type with a poor prognosis.

[0010] Therefore, in order to diagnose major mental illnesses such as depression, bipolar disorder, or schizophrenia more objectively and accurately, it is necessary to go beyond clinical symptom analysis and conduct imaging evaluations based on neurological and EEG tests, as well as hematological evaluations based on biomarkers.

[0011] In this regard, a prior art document for diagnosing treatment-resistant depression using brain MRI images is “Method for diagnosing treatment-resistant depression using brain MRI analysis” (hereinafter referred to as “prior art”), Korean Patent Publication No. 10-0425525, in which the inventor of the present invention participated as an inventor.

[0012] However, in the case of existing technologies for diagnosing major mental illnesses such as depression, bipolar disorder, or schizophrenia, including conventional technologies, biomarkers with a significant level of performance and technologies for utilizing them as indicators for diagnosing major mental illnesses such as depression, bipolar disorder, or schizophrenia have not been presented.

[0013] The present invention was created to solve the above problems, and the purpose of the present invention is to provide a biomarker and techniques for utilizing the same that can produce significant results in diagnosing major mental illnesses such as depression, bipolar disorder, or schizophrenia.

[0014]

[0015] In order to achieve the above purpose, the biomarker composition for distinguishing between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia of the present invention includes leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in a serum sample.

[0016] Meanwhile, as another embodiment for achieving the above purpose, the composition for distinguishing between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia of the present invention includes a preparation for measuring the expression level of each of five proteins of biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia, including leptin, TNF-α (Tumor Necrosis Factor-α), PAI-1 (Plasminogen activator inhibitor-1), IL-6 (InterLeukin-6), and BDNF (Brain-Derived Neurotrophic Factor) in a serum sample.

[0017] Here, the preparation for measuring the expression level of each of the five proteins of the biomarkers for distinguishing between the above mood disorder type mental illness and schizophrenia provides information necessary for calculating an estimate (X) of the probability of being diagnosed with schizophrenia compared to mood disorder type mental illness using the following mathematical formula 1.

[0018] [Mathematical Formula 1]

[0019] X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)}

[0020] (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1))

[0021] And as another embodiment for achieving the above purpose, the diagnostic kit for distinguishing between mood disorder-type mental illness and schizophrenia of the present invention includes the composition for distinguishing between mood disorder-type mental illness and schizophrenia described above.

[0022] Finally, as another embodiment for achieving the above purpose, a method for providing information for distinguishing between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia includes: Step A for detecting a serum sample as a biological sample from an individual subject; Step B for measuring the expression level of each of five proteins of biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia, including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF), in the serum sample detected through Step A; and Step C for calculating an estimated value (X) of the probability of being diagnosed with schizophrenia versus mood disorder-type mental illness by inputting information on the expression level of each of five proteins of biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia measured through Step B into the following mathematical formula 1.

[0023] [Mathematical Formula 1]

[0024] X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)}

[0025] (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1))

[0026] Here, the method for providing information for distinguishing between the above mood disorder mental illness and schizophrenia further includes a D step in which the closer the estimated value (X) of the probability of being diagnosed with schizophrenia compared to the mood disorder mental illness calculated through the C step is to -∞, the higher the likelihood of being diagnosed with the mood disorder mental illness corresponding to depression and bipolar disorder, and the closer it is to ∞, the higher the likelihood of being diagnosed with schizophrenia.

[0027]

[0028] According to the present invention, the following effects are achieved.

[0029] First, we present a biomarker composition that can be significantly utilized to differentiate between mood disorder-type psychosis and schizophrenia.

[0030] Second, a composition that can be used as a diagnostic kit and for providing information for diagnosis can be provided, including a preparation that measures the expression level of each of the five proteins of the biomarker composition.

[0031] Third, by calculating an estimate of the probability of being diagnosed with schizophrenia compared to mood disorder-type mental illness, information is provided for distinguishing mood disorder-type mental illness from schizophrenia based on this information, and objective diagnosis of mood disorder-type mental illness and schizophrenia from a hematological perspective is possible.

[0032]

[0033] Figures 1 and 2 are graphs showing the results of analyzing the expression level of each biomarker in a serum sample of an individual using a composition for distinguishing between mood disorder-type mental illness and schizophrenia.

[0034] Figures 3 to 7 are graphs showing the ROC curve pattern for confirming the diagnostic ability of each biomarker in a serum sample of an individual subject for schizophrenia compared to mood disorder-type mental illness using a composition for distinguishing between mood disorder-type mental illness and schizophrenia.

[0035] Figure 8 is a graph showing the results of analyzing the comprehensive expression level of all biomarkers in serum samples of subjects using a composition for distinguishing between mood disorder-type mental illness and schizophrenia.

[0036] Figure 9 is a graph showing the ROC curve pattern for confirming the diagnostic ability of schizophrenia compared to mood disorder-type mental illness for all biomarkers in a serum sample of an individual using a composition for distinguishing mood disorder-type mental illness and schizophrenia.

[0037] Figures 10 to 12 are reference diagrams for explaining the method of proceeding with the biomarker expression level measurement step during the process of conducting an experiment related to providing information and diagnosis for differentiating between mood disorder-type mental illness and schizophrenia using a composition for differentiating between mood disorder-type mental illness and schizophrenia.

[0038] According to one embodiment of the present invention, in a biomarker composition for distinguishing between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia,

[0039] Provided is a biomarker composition for distinguishing between mood disorder-type mental illness and schizophrenia, characterized by including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in a serum sample.

[0040] According to one embodiment of the present invention, in a composition for distinguishing between mood disorder-type mental illness and schizophrenia for measuring the expression level of a biomarker for distinguishing between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia,

[0041] A composition for distinguishing between mood disorder-type mental illness and schizophrenia is provided, characterized by including a preparation for measuring the expression level of each of five proteins of biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia, including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in a serum sample.

[0042] According to one embodiment of the present invention, a preparation for measuring the expression level of each of the five proteins of the biomarker for distinguishing between mood disorder-type mental illness and schizophrenia is characterized in that it provides information necessary for calculating an estimate (X) of the probability of being diagnosed with schizophrenia compared to mood disorder-type mental illness using the following mathematical formula 1:

[0043] [Mathematical Formula 1]

[0044] X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)}

[0045] (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1))

[0046] According to one embodiment of the present invention, a diagnostic kit for distinguishing between mood disorder-type mental illness and schizophrenia is provided, characterized in that it includes a composition for distinguishing between mood disorder-type mental illness and schizophrenia.

[0047] According to one embodiment of the present invention, a method is provided for providing information necessary to distinguish between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia, comprising the following steps:

[0048] Step A: Detecting a serum sample as a biological sample from an individual subject;

[0049] Step B, which measures the expression level of each of the five proteins of biomarkers for distinguishing mood disorder-type mental illness and schizophrenia, including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in the serum sample detected through the above step A; and

[0050] Step C: calculating an estimate (X) of the probability of being diagnosed with schizophrenia versus mood disorder by inputting information on the expression level of each of the five proteins of the biomarker for distinguishing between mood disorder-type mental illness and schizophrenia measured through the above step B into the following mathematical formula 1.

[0051] [Mathematical Formula 1]

[0052] X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)}

[0053] (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1))

[0054] The method of providing information for distinguishing between the above mood disorder type mental illness and schizophrenia is as follows:

[0055] It is characterized by further including a D stage in which the closer the estimated value (X) of the probability of being diagnosed as schizophrenia compared to a mood disorder mental illness produced through the above C stage is to -∞, the higher the probability of being diagnosed as a mood disorder mental illness corresponding to depression and bipolar disorder, and the closer it is to ∞, the higher the probability of being diagnosed as schizophrenia.

[0056] In this way, by using a biomarker composition that can be significantly utilized for distinguishing between mood disorder-type mental illness and schizophrenia according to the present invention, an estimate of the probability of being diagnosed with schizophrenia compared to mood disorder-type mental illness is calculated, and based on the information, information for distinguishing between mood disorder-type mental illness and schizophrenia is provided, and objective diagnosis of mood disorder-type mental illness and schizophrenia from a hematological perspective is enabled.

[0057] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in various different embodiments and is not limited to the embodiments described herein.

[0058]

[0059] 1. Description of biomarkers for differentiating mood disorders from schizophrenia.

[0060] The present invention proposes a biomarker related to the diagnosis of schizophrenia compared to mood disorder-type mental illness in the blood, and based on this, a method can be utilized to classify, identify, and monitor mental illness types according to the expression pattern of the biomarker.

[0061] The mood disorder mental illness described below is a term that comprehensively refers to two diseases corresponding to depression and bipolar disorder, and it is assumed that a technique is presented to distinguish between the first comparable subject corresponding to depression and bipolar disorder and the second comparable subject corresponding to schizophrenia.

[0062] Specifically, the biomarker composition for distinguishing between mood disorder-type mental illness and schizophrenia includes leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in serum samples.

[0063] As biomarkers corresponding to these five proteins, leptin, TNF-α (Tumor Necrosis Factor-α), PAI-1 (Plasminogen activator inhibitor-1), IL-6 (InterLeukin-6), and BDNF (Brain-Derived Neurotrophic Factor) in serum samples can obtain concentration information indicating the degree of expression by bead-based multiplex immunoassay (Luminex).

[0064] To this end, the composition for distinguishing between mood disorder-type mental illness and schizophrenia includes a preparation for measuring the expression level of each of five proteins of biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia, including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in a serum sample.

[0065] As explained above, the expression level of each of the five proteins of the biomarker for distinguishing between mood disorder and schizophrenia is analyzed by the bead-based multiplex immunoassay (Luminex). The preparations included herein include beads that form a primary complex in the form of an 'antibody-antigen' and are first bound to the biomarker, as well as components such as antibodies that are equipped with biotin to the primary complex to form a secondary complex, and streptavidin-conjugated phycoerythrin (PE) that is equipped with a fluorescent substance and binds to the biotin of the antibody used to form the secondary complex to form the final complex.

[0066] A preparation that measures the expression level of each of the five proteins of biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia can provide information necessary for calculating an estimate (X) of the probability of being diagnosed with schizophrenia versus mood disorder-type mental illness using mathematical formula 1.

[0067] Specifically, mathematical expression 1 is defined as 'X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)}'. (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1))

[0068] Furthermore, by utilizing a preparation that measures the expression levels of each of the five proteins that are biomarkers for differentiating between mood disorder-type mental illness and schizophrenia, a diagnostic kit for differentiating between mood disorder-type mental illness and schizophrenia can also be expanded and implemented.

[0069] 2. Information provision and explanation of diagnostic experiments for differentiating mood disorder from schizophrenia.

[0070] Below, the process of providing information and diagnosing mood disorder and schizophrenia using proteins selected as biomarkers for distinguishing mood disorder and schizophrenia corresponding to depression and bipolar disorder according to the present invention is sequentially explained based on an example of an actual experiment, through a series of processes.

[0071] (1) Sample detection stage (Stage A)

[0072] First, the clinical trial subjects who were to be subjected to sample detection were selected, and the process of detecting and collecting serum samples as biological samples from the selected patients (subjects) was carried out.

[0073] Specifically, serum samples from 217 patients with mood disorder (114 patients with depression and 103 patients with bipolar disorder) and 106 patients with schizophrenia were provided by Seoul National University Hospital. The patients with depression were aged 19 to 65 years with an average age of 42 years, the patients with bipolar disorder were aged 19 to 62 years with an average age of 34 years, and the patients with schizophrenia were aged 19 to 60 years with an average age of 38 years.

[0074] Serum samples from 114 patients with depression, 103 patients with bipolar disorder, and 106 patients with schizophrenia were collected from peripheral blood, stored at room temperature for 1 hour, centrifuged, and the supernatant was collected. These serum samples were stored at -80℃ until use.

[0075] (2) Biomarker expression level measurement step (Step B)

[0076] In this step, the expression levels of each of the five proteins, which are biomarkers for distinguishing mood disorder and schizophrenia, including leptin, TNF-α (Tumor Necrosis Factor-α), PAI-1 (Plasminogen activator inhibitor-1), IL-6 (InterLeukin-6), and BDNF (Brain-Derived Neurotrophic Factor), are measured in the serum sample detected through the previously performed sample detection step (Step A).

[0077] Specifically, serum samples collected after detection from 114 patients with depression, 103 patients with bipolar disorder, and 106 patients with schizophrenia were subjected to concentration information indicating the degree of expression by bead-based multiplex immunoassay (Luminex).

[0078] The concentrations of five proteins corresponding to leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) were measured using the Milliplex Map Kit (Luminex kit) from Merck, and analyses were performed in a 96-well plate according to each protocol.

[0079] - Preparation of standard materials

[0080] For each standard material (standard protein, Standard) prepared as shown in Table 1 below, 50 μl of standard material A and 450 μl of standard material B are added to one microcentrifuge tube, mixed well by vortexing, and labeled as ‘Standard material 1’. Then, 100 μl of standard material B is added to seven microcentrifuge tubes, and labeled as “Standard material 2 to Standard material 7” and “Blank”.

[0081] Here, standard material A refers to standard material A: an integrated high-concentration target material produced by combining five standard materials (leptin, TNF-α, PAI-1, IL-6, BDNF) at specific concentrations.

[0082] In addition, standard material B refers to standard material B: an integrated low-concentration target material produced by combining five standard materials (leptin, TNF-α, PAI-1, IL-6, BDNF) at specific concentrations, or a biological base material produced using distilled water or a buffer material.

[0083] Dispense 100 μl of the mixture in the tube labeled ‘Standard Material 1’ into the tube labeled ‘Standard Material 2’ and vortex.

[0084] In this manner, as shown in FIG. 11, 100 μl of the mixture in the tube labeled as 'standard material 2' is sequentially dispensed into the tube labeled as 'standard material 3' and vortexed, 100 μl of the mixture in the tube labeled as 'standard material 3' is sequentially dispensed into the tube labeled as 'standard material 4' and vortexed, 100 μl of the mixture in the tube labeled as 'standard material 4' is sequentially dispensed into the tube labeled as 'standard material 5' and vortexed, 100 μl of the mixture in the tube labeled as 'standard material 5' is sequentially dispensed into the tube labeled as 'standard material 6' and vortexed, and 100 μl of the mixture in the tube labeled as 'standard material 6' is sequentially dispensed into the tube labeled as 'standard material 7' and vortexed.

[0085]

[0086] - As shown in Figure 12 for preparing serum sample dilution, dispense 60 μl of standard materials 1 to 7 and blank sequentially through the [Standard material preparation] process described above into column 1 of the dilution plate.

[0087] Next, dispense 45 μl of Assay buffer and 5 μl of serum samples (up to 80 samples) in order from rows 3 to 12 of the dilution plate according to the number of tests.

[0088] - Preparation of capture antibody (magnetic bead conjugated antibody)

[0089] First, vortex each marker tube of the capture antibody and then disperse it using an ultrasonic cleaner for 1 minute.

[0090] Next, add 400 μl of each marker of the capture antibody to the mixing container.

[0091] Next, add Assay buffer to the mixing container until the volume reaches 4.0 ml and vortex.

[0092] - Busy process in progress

[0093] Standard materials 1 to 7 and blank in column 1 of the dilution plate shown in Figure 12 are dispensed in 25 μl each into columns 1 and 2 of the 96-well plate for analysis as shown in Figure 13.

[0094] Dispense 25 μl of the diluted serum samples (up to 80 samples) prepared in the previously described [Serum Sample Dilution Preparation] process sequentially into rows 3 to 12 of a 96-well plate for analysis.

[0095] Next, dispense 25 μl of the Capture antibody solution (4 ml) prepared in the [Capture antibody (Magnetic bead conjugated antibody) preparation] process according to the number of tests into rows 1 to 12 of the 96-well plate for analysis.

[0096] - Stirring process in progress

[0097] First, the 96-well plate for analysis as shown in Fig. 13 is shaken at 800 rpm for 2 hours at room temperature in an orbital shaker, then the 96-well plate for analysis is taken out from the orbital shaker and 25 μl of detection antibody is dispensed.

[0098] Next, shake the 96-well plate for analysis on an orbital shaker at 800 rpm for 1 hour at room temperature, then take the 96-well plate for analysis out of the orbital shaker again and dispense 25 μl of SA-PE solution.

[0099] Next, the 96-well plate for analysis is stirred at 800 rpm for 30 minutes at room temperature on an orbital shaker to complete the reaction.

[0100] - Cleaning and measurement preparation process in progress

[0101] First, turn on the microplate washer and place the 96-well plate for analysis on it for 1 minute to precipitate the results.

[0102] After this, remove the supernatant from the 96-well plate for analysis using a microplate washer, and then take the 96-well plate for analysis out of the microplate washer.

[0103] Next, pipette 200 μl of washing buffer into each well of a 96-well plate for analysis, gently tap the sides of the 96-well plate for analysis for 10 seconds to suspend the resulting reactants, and then place it on a microplate washer for 1 minute to sediment the resulting products.

[0104] Then, remove the supernatant from the wells of the 96-well plate for analysis using the microplate washer, and then take the 96-well plate for analysis out of the microplate washer.

[0105] Again, pipette 200 μl of Washing Buffer into each well of the 96-well plate for analysis, gently tap the sides of the 96-well plate for analysis for 10 seconds to suspend the resulting reactants, then place it on the Microplate washer for 1 minute to sediment the resulting products, and as previously done, remove the supernatant from the 96-well plate for analysis using the Microplate washer, and then take the 96-well plate for analysis out of the Microplate washer.

[0106] Once more, pipette 200 μl of Washing Buffer into each well of the 96-well plate for analysis, gently tap the sides of the 96-well plate for analysis for 10 seconds to suspend the resulting reactants, then place it on a microplate washer for 1 minute to sediment the resulting products, and as previously described, remove the supernatant from the 96-well plate for analysis using a microplate washer to complete the washing.

[0107] After this washing process is completed, pipette 100 μl of sheath fluid into each well of a 96-well plate for analysis, shake the 96-well plate for analysis on an orbital shaker at 800 rpm for 5 minutes at room temperature, and prepare for measurement.

[0108] Finally, the results were calculated by performing analysis on the Luminex 200 System.

[0109] As a result, the concentration values ​​representing the expression levels of each of the five proteins of biomarkers for distinguishing between mood disorder-type psychosis and schizophrenia, including Eotaxin, Nerve growth factors (NGF), Tumor Necrosis Factor-α (TNF-α), Glial cell Derived Neurotrophic Factor (GDNF), Interleukin-1β (IL-1β), and Serum soluble CD40 Ligand (sCD40L) in serum samples, are numerically informationized.

[0110] In fact, the protein concentration values ​​of leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) expressed in each of the serum samples collected after detection from 114 patients with depression, 103 patients with bipolar disorder, and 106 patients with schizophrenia are as shown in Figures 1 and 2.

[0111] As shown in Figures 1 and 2, the expression levels of biomarkers of leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in serum samples from the first experimental group (Bipolar+Depression, BP+DP) of 114 patients with depression and 103 patients with bipolar disorder, and the second experimental group (Schizophrenia, SZ) of 106 patients with schizophrenia, show differences from each other.

[0112] In addition, we analyzed the diagnostic ability of schizophrenia compared to mood disorder-type mental illness for each of the five proteins of biomarkers for distinguishing mood disorder-type mental illness and schizophrenia, whose expression levels were analyzed using the concentration values ​​in the serum samples of Figures 1 and 2.

[0113] Specifically, the diagnostic ability of the five proteins of the biomarker for distinguishing between mood disorder and schizophrenia was confirmed through the Receiver Operating Characteristic (ROC) curve, which shows the false positive rate (FPR, 1-specificity, X-axis value) and true positive rate (TPR, sensitivity, Y-axis value) for multiple decision criteria (operating conditions, cutoff, decision threshold, positive judgment criteria) based on the diagnostic test results, based on the sensitivity and specificity (1-specificity) measured during the actual diagnosis process.

[0114] As a result, in the case of Leptin as a single biomarker, the ROC curve result was shown as in Figure 3, and the AUC (Area under the ROC curve) showed a value of 0.7542.

[0115] In addition, as a single biomarker, TNF-α (Tumor Necrosis Factor-α) showed an AUC value of 0.6755 through the results of the ROC curve as shown in Figure 4, and PAI-1 (Plasminogen activator inhibitor-1) showed an AUC value of 0.843 through the results of the ROC curve as shown in Figure 5.

[0116] Additionally, as a single biomarker, IL-6 (InterLeukin-6) showed an AUC value of 0.5846 through the results of the ROC curve as shown in Figure 6, and BDNF (Brain-Derived Neurotrophic Factor) showed an AUC value of 0.6951 through the results of the ROC curve as shown in Figure 7.

[0117] (3) Estimation calculation stage (Stage C)

[0118] In this step, the information on the expression level of each of the five proteins of the biomarker for distinguishing between mood disorder-type mental illness and schizophrenia, measured through the previously performed biomarker expression level measurement step (Step B), is input into the following mathematical formula 1 to calculate the estimated probability (X) of being diagnosed with schizophrenia versus mood disorder-type mental illness.

[0119] Specifically, mathematical expression 1 is defined as 'X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)}'. (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1))

[0120] Here, the variable values ​​for the concentrations of leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in the serum sample included in mathematical formula 1 can be measured through the previously performed biomarker expression level measurement step (step B) and provided in the form of information.

[0121] Specifically, the X value as a result value produced through mathematical expression 1 is an estimate of the probability of being diagnosed with schizophrenia compared to mood disorder-type mental illness, and becomes a distinguishing indicator information that can be used to classify mood disorder-type mental illness and schizophrenia.

[0122] Therefore, in this stage, the biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia, including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF), can be combined and the ability to distinguish between mood disorder-type mental illness and schizophrenia can be evaluated through regression analysis.

[0123] As a result, the expression levels of all five proteins of the biomarkers for distinguishing between mood disorder and schizophrenia in the comprehensive serum samples were clearly distinguished when compared between the first experimental group (Bipolar+Depression, BP+DP) of 114 patients with depression and 103 patients with bipolar disorder and the second experimental group (Schizophrenia, SZ) of 106 patients with schizophrenia, as shown in Figure 8.

[0124] Above all, the comprehensive diagnostic ability of all five proteins of the biomarker for distinguishing between mood disorder and schizophrenia is confirmed through the ROC (Receiver Operating Characteristic) curve, which shows the false positive rate (FPR, 1-specificity, X-axis value) and true positive rate (TPR, sensitivity, Y-axis value) for multiple decision criteria (operating condition, cutoff, decision threshold, positive judgment criteria) based on the diagnostic test results. It shows a specificity of 83.6% and a sensitivity of 84.1%, and in particular, it shows an AUC value of 0.901 through the results of the ROC curve as shown in Figure 9, showing excellent diagnostic performance.

[0125] (4) Estimate result analysis stage (Stage D)

[0126] In this step, the closer the estimate (X) of the probability of being diagnosed with schizophrenia compared to mood disorder mental illness calculated through the previously performed estimate calculation step (Step C) is to -∞, the higher the probability of being diagnosed with mood disorder mental illness corresponding to depression and bipolar disorder, and the closer it is to ∞, the higher the probability of being diagnosed with schizophrenia.

[0127] As a result, by using the proteins selected as biomarkers for distinguishing between mood disorder-type mental illness and schizophrenia of the present invention and going through a series of processes described above, an indicator is provided for diagnosing the patient's mental illness as mood disorder-type mental illness or schizophrenia, thereby proving that the use of hematological biomarkers for mental illness is possible.

[0128] The embodiments disclosed in the present invention are intended to illustrate, not limit, the technical concepts of the present invention. These embodiments do not limit the scope of the technical concepts of the present invention. The scope of protection should be interpreted according to the following claims, and all technical concepts within the scope equivalent thereto should be construed as being included within the scope of the present invention.

[0129]

[0130] First, we present a biomarker composition that can be significantly utilized to differentiate between mood disorder-type psychosis and schizophrenia.

[0131] Second, a composition that can be used as a diagnostic kit and for providing information for diagnosis can be provided, including a preparation that measures the expression level of each of the five proteins of the biomarker composition.

[0132] Third, by calculating an estimate of the probability of being diagnosed with schizophrenia compared to mood disorder-type mental illness, information is provided for distinguishing mood disorder-type mental illness from schizophrenia based on this information, and objective diagnosis of mood disorder-type mental illness and schizophrenia from a hematological perspective is possible.

Claims

1. In a biomarker composition for differentiating between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia, Characterized by containing leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in serum samples. Biomarker composition for differentiating mood disorder and schizophrenia.

2. In a composition for distinguishing between mood disorder-type mental illness and schizophrenia, for measuring the expression level of a biomarker for distinguishing between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia, A composition comprising a preparation for measuring the expression level of each of five proteins of biomarkers for distinguishing mood disorder and schizophrenia, including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in a serum sample. A composition for differentiating mood disorder and schizophrenia.

3. In paragraph 2, The preparation for measuring the expression level of each of the five proteins of the biomarkers for distinguishing between the above mood disorder type mental illness and schizophrenia is characterized in that it provides information necessary for calculating an estimate (X) of the probability of being diagnosed with schizophrenia compared to mood disorder type mental illness using the following mathematical formula 1. A composition for differentiating mood disorder and schizophrenia. [Mathematical Formula 1] X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)} (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1)) 4. Characterized in that it comprises a composition for distinguishing between mood disorder-type mental illness and schizophrenia according to Article 2 or 3. Diagnostic kit for differentiating mood disorder and schizophrenia.

5. In a method for providing information necessary to distinguish between mood disorder-type mental illness corresponding to depression and bipolar disorder and schizophrenia, Step A: Detecting a serum sample as a biological sample from an individual subject; Step B, which measures the expression level of each of the five proteins of biomarkers for distinguishing mood disorder-type mental illness and schizophrenia, including leptin, tumor necrosis factor-α (TNF-α), plasminogen activator inhibitor-1 (PAI-1), interleukin-6 (IL-6), and brain-derived neurotrophic factor (BDNF) in the serum sample detected through the above step A; and It is characterized by including a step C for calculating an estimated value (X) of the probability of being diagnosed with schizophrenia compared to mood disorder mental illness by inputting information on the expression level of each of the five proteins of the biomarker for distinguishing between mood disorder mental illness and schizophrenia measured through the above step B into the following mathematical formula 1. Information provision method for differentiating mood disorder and schizophrenia. [Mathematical Formula 1] X=α+{β1×(concentration of leptin in serum sample)}+{β2×(concentration of TNF-α in serum sample)}+{β3×(concentration of PAI-1 in serum sample)}+{β4×(concentration of IL-6 in serum sample)}+{β5×(concentration of BDNF in serum sample)} (X: Estimated probability of being diagnosed with schizophrenia versus mood disorder, α: Intercept value when the estimate (X) is 0 (-10≤α≤10), β1: Regression coefficient representing the weight for the concentration value of leptin in the serum sample (-1≤β1 ≤1), β2: Regression coefficient representing the weight for the concentration value of TNF-α in the serum sample (-1≤β2≤1), β3: Regression coefficient representing the weight for the concentration value of PAI-1 in the serum sample (-1≤β3≤1), β4: Regression coefficient representing the weight for the concentration value of IL-6 in the serum sample (-1≤β4≤1), β5: Regression coefficient representing the weight for the concentration value of BDNF in the serum sample (-1≤β5≤1)) 6. In paragraph 5, The method of providing information for distinguishing between the above mood disorder type mental illness and schizophrenia is as follows: It is characterized by further including a D stage that diagnoses that the closer the estimated value (X) of the probability of being diagnosed as schizophrenia compared to a mood disorder mental illness produced through the above C stage is to -∞, the higher the probability of being diagnosed as a mood disorder mental illness corresponding to depression and bipolar disorder, and the closer it is to ∞, the higher the probability of being diagnosed as schizophrenia. Information provision method for differentiating mood disorder and schizophrenia.

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